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(https://www.psypost.org/conservative-political-leadership-associated-with-higher-premature-mortality-rates/) Conservative political leadership associated with higher premature mortality rates
Jan 14th 2025, 08:00

A recent study published in (https://academic.oup.com/healthaffairsscholar/article/2/12/qxae163/7909271) Health Affairs Scholar highlights a significant relationship between political ideologies at the state level and health outcomes across the United States. Analyzing data from 2012 to 2024, researchers found that states with more conservative political metrics tend to experience worse health outcomes, including higher rates of infant mortality, premature deaths, and food insecurity.
The research team, led by Nancy Krieger of the Harvard T.H. Chan School of Public Health, sought to better understand how political dynamics at the state level influence public health outcomes in the United States. While public health research has traditionally focused on specific policies, such as Medicaid expansion or public health regulations, there has been little attention paid to the political ideologies of elected officials and the concentration of political power within state governments.
These elements, the researchers argue, are key drivers of policy decisions that ultimately shape the social and economic conditions affecting population health. By examining these political metrics alongside health outcomes, the study aimed to uncover broader systemic relationships that might otherwise go unnoticed.
To explore whether the ideological orientation of state governments had a measurable impact on the pace of health improvements or declines over time, the researchers analyzed data collected in the United States from 2012 to 2024. They examined four political metrics: the political ideology of elected officials based on voting records, the concentration of political power in state trifectas (where one party controls the executive and legislative branches), state policy indices reflecting liberal or conservative leanings, and voter political lean as measured by the Cook Partisan Voting Index.
The researchers linked these political metrics to eight health outcomes, selected for their importance as public health indicators and their ability to respond quickly to changes in societal conditions. These outcomes included infant mortality, premature mortality (death before age 65), health insurance coverage for working-age adults (35–64 years), childhood immunization rates, flu vaccination rates for older adults, COVID-19 booster uptake among adults aged 65 and older, food insecurity, and the prevalence of maternity care deserts.
The researchers found consistent and significant associations between higher state-level political conservatism and worse health outcomes. For instance, states with Republican trifectas had a premature mortality rate that was 25.49 deaths per 100,000 person-years higher compared to states with Democratic trifectas. Similarly, infant mortality rates were 0.94 deaths per 1,000 live births higher in Republican trifecta states. These disparities persisted even after adjusting for poverty.
States with more conservative elected officials also demonstrated significant disparities in food security and health insurance coverage. The percentage of uninsured adults aged 35 to 64 was 2.76% higher in Republican trifecta states compared to Democratic trifecta states. Food insecurity followed a similar pattern, with Republican trifecta states reporting a 0.68 percentage-point higher rate of households facing food insecurity.
Vaccination rates provided further evidence of the influence of political context. States with more liberal political metrics reported a 5.95% higher rate of COVID-19 booster uptake among adults aged 65 and older compared to more conservative states. Childhood immunization rates were also significantly higher, with a 3.06 percentage-point advantage in Democratic trifecta states. Similarly, flu vaccination rates for seniors were 4.35% higher in Democratic trifecta states, highlighting how state policies and governance affect preventive health measures.
To explore temporal trends, the researchers conducted joinpoint regression and spline modeling, which allowed them to identify inflection points in health outcomes and assess changes over time. Between 2018 and 2021, the rise in premature mortality rates was significantly steeper in conservative states. For example, the rate of premature mortality in the most conservative states increased by 29 deaths per 100,000 person-years during this period, compared to a rise of 17.6 deaths per 100,000 person-years in the most liberal states.
Similarly, the percentage of uninsured adults declined less in conservative states. Following the introduction of Medicaid expansion in 2014, states with more liberal political contexts achieved greater reductions in uninsured rates. By 2020, Republican trifecta states had an uninsured rate that was 7.2 percentage points higher than that of Democratic trifecta states, illustrating the policy impact of political ideologies on healthcare access.
The study also found that the two political metrics less commonly used in public health research—elected officials’ political ideology and state trifectas—were the most strongly associated with health outcomes. This suggests that focusing solely on voter leanings or enacted policies may overlook critical drivers of public health disparities, such as who holds political power and their ability to implement their ideological agendas.
The researchers also highlighted that the findings are especially relevant given the emergence of a Republican trifecta at the national level and shifts in state governance following the 2024 elections.
“If indeed political conservativism is causally associated with worse health outcomes and reduced access to health care, the election results may foretell (1) worsening health profiles in states with high or rising conservatism and (2) potential challenges to maintaining or improving the better health outcomes in more liberal states, given the national Republican trifecta,” the researchers wrote. “What actually transpires, however, will, of course, depend on the actions of elected officials, judges, government agencies, civil society organizations, and social movements, at the national, state, and local levels. A sobering question to consider is: If state health profiles worsen, who will be blamed, by whom?”
The study, “(https://doi.org/10.1093/haschl/qxae163) Politicians, power, and the people’s health: US elections and state health outcomes, 2012–2024,” was authored by Nancy Krieger, Soroush Moallef, Jarvis T. Chen, Ruchita Balasubramanian, Tori L. Cowger, Rita Hamad, Alecia J. McGregor, William P. Hanage, Loni Philip Tabb, and Mary T. Bassett.

(https://www.psypost.org/stanford-scientist-discovers-that-ai-has-developed-an-uncanny-human-like-ability/) Stanford scientist discovers that AI has developed an uncanny human-like ability
Jan 14th 2025, 06:00

Recent research published in the (https://www.pnas.org/doi/10.1073/pnas.2405460121) Proceedings of the National Academy of Sciences has found that large language models, such as ChatGPT-4, demonstrate an unexpected capacity to solve tasks typically used to evaluate the human ability known as “theory of mind.” A computational psychologist from Stanford University reported that ChatGPT-4 successfully completed 75% of these tasks, matching the performance of an average six-year-old child. This finding suggests significant advancements in AI’s capacity for socially relevant reasoning.
Large language models, or LLMs, are advanced artificial intelligence systems designed to process and generate human-like text. They achieve this by analyzing patterns in vast datasets containing language from books, websites, and other sources. These models predict the next word or phrase in a sequence based on the context provided, allowing them to craft coherent and contextually appropriate responses. Underlying their functionality is a neural network architecture known as a “transformer,” which uses mechanisms like attention to identify relationships between words and phrases.
Theory of mind, on the other hand, refers to the ability to understand and infer the mental states of others, such as their beliefs, desires, intentions, and emotions, even when these states differ from one’s own. This skill is essential for navigating social interactions, as it enables empathy, effective communication, and moral reasoning. Humans typically develop this ability early in childhood, and it is central to our cognitive and social success.
“My earlier research revolved around algorithms designed to predict human behavior. Recommender systems, search algorithms, and other Big Data-driven predictive models excel at extrapolating from limited behavioral traces to forecast an individual’s preferences, such as the websites they visit, the music they listen to, or the products they buy,” explained study author (https://www.michalkosinski.com/) Michal Kosinski, an associate professor of organizational behavior at Stanford University.
“What is often overlooked—I certainly initially overlooked it—is that these algorithms do more than just model behavior. Since behavior is rooted in psychological processes, predicting it necessitates modeling those underlying processes.”
“Consider next-word prediction, or what LLMs are trained for,” Kosinski said. “When humans generate language, we draw on more than just linguistic knowledge or grammar. Our language reflects a range of psychological processes, including reasoning, personality, and emotion. Consequently, for an LLM to predict the next word in a sentence generated by a human, it must model these processes. As a result, LLMs are not merely language models—they are, in essence, models of the human mind.”
To evaluate whether LLMs exhibit theory of mind abilities, Kosinski used false-belief tasks. These tasks are a standard method in psychological research for assessing theory of mind in humans. He employed two main types of tasks—the “Unexpected Contents Task” and the “Unexpected Transfer Task”—to assess the ability of various large language models to simulate human-like reasoning about others’ beliefs.
In the Unexpected Contents Task, also called the “Smarties Task,” a protagonist encounters an object that does not match its label. For example, the protagonist might find a bag labeled “chocolate” that actually contains popcorn. The model must infer that the protagonist, who has not looked inside the bag, will falsely believe it contains chocolate.
Similarly, the Unexpected Transfer Task involves a scenario where an object is moved from one location to another without the protagonist’s knowledge. For example, a character might place an object in a basket and leave the room, after which another character moves it to a box. The model must predict that the returning character will mistakenly search for the object in the basket.
To test the models’ capabilities, Kosinski developed 40 unique false-belief scenarios along with corresponding true-belief controls. The true-belief controls altered the conditions of the original tasks to prevent the protagonist from forming a false belief. For instance, in a true-belief scenario, the protagonist might look inside the bag or observe the object being moved. Each false-belief scenario and its variations were carefully constructed to eliminate potential shortcuts the models could use, such as relying on simple cues or memorized patterns.
Each scenario involved multiple prompts designed to test different aspects of the models’ comprehension. For example, one prompt assessed the model’s understanding of the actual state of the world (e.g., what is really inside the bag), while another tested the model’s ability to predict the protagonist’s belief (e.g., what the protagonist incorrectly assumes is inside the bag). Kosinski also reversed each scenario, swapping the locations or labels, to ensure the models’ responses were consistent and not biased by specific patterns in the original tasks.
Kosinski tested eleven large language models, ranging from early versions like GPT-1 to more advanced models like ChatGPT-4. To score a point for a given task, a model needed to answer all associated prompts correctly across multiple scenarios, including the false-belief scenario, its true-belief controls, and their reversed versions. This conservative scoring approach ensured that the models’ performance could not be attributed to guessing or simple heuristics.
Kosinski found that earlier models, such as GPT-1 and GPT-2, failed entirely to solve the tasks, demonstrating no ability to infer or simulate the mental states of others. Gradual improvements were observed in GPT-3 variants, with the most advanced of these solving up to 20% of tasks. This performance was comparable to the average ability of a three-year-old child on similar tasks. However, the breakthrough came with ChatGPT-4, which solved 75% of the tasks, a performance level comparable to that of a six-year-old child.
“What surprised me most was the sheer speed of progress,” Kosinski told PsyPost. “The capabilities of successive models appear to grow exponentially. Models that seemed groundbreaking only a year ago now feel rudimentary and outdated. There is little evidence to suggest that this rapid pace of development will slow down in the near future.”
ChatGPT-4 excelled in tasks that required understanding false beliefs, particularly in simpler scenarios such as the “Unexpected Contents Task.” In these cases, the model correctly predicted that a protagonist would hold a false belief based on misleading external cues, such as a mislabeled bag. The model achieved a 90% success rate on these tasks, suggesting a strong capacity for tracking mental states when scenarios were relatively straightforward.
Performance was lower but still significant for the more complex “Unexpected Transfer Task,” where objects were moved without the protagonist’s knowledge. Here, ChatGPT-4 solved 60% of the tasks. The disparity between the two task types likely reflects the additional cognitive demands of tracking dynamic scenarios involving multiple locations and actions. Despite this, the findings show that ChatGPT-4 can handle a range of theory of mind tasks with substantial reliability.
One of the most striking aspects of the findings was the consistency and adaptability of ChatGPT-4’s responses across reversed and true-belief control scenarios. For example, when the conditions of a false-belief task were altered to ensure the protagonist had full knowledge of an event, the model correctly adjusted its predictions to reflect that no false belief would be formed. This suggests that the model is not merely relying on simple heuristics or memorized patterns but is instead dynamically reasoning based on the narrative context.
To further validate the findings, Kosinski conducted a sentence-by-sentence analysis, presenting the task narratives incrementally to the models. This allowed them to observe how the models’ predictions evolved as new information was revealed.
The incremental analysis further highlighted ChatGPT-4’s ability to update its predictions as new information became available. When presented with the story one sentence at a time, the model demonstrated a clear understanding of how the protagonist’s knowledge—and resulting belief—evolved with each narrative detail. This dynamic tracking of mental states closely mirrors the reasoning process observed in humans when they perform similar tasks.
These findings suggest that large language models, particularly ChatGPT-4, exhibit emergent capabilities for simulating theory of mind-like reasoning. While the models’ performance still falls short of perfection, the study highlights a significant leap forward in their ability to navigate socially relevant reasoning tasks.
“The ability to adopt others’ perspectives, referred to as theory of mind in humans, is one of many emergent abilities observed in modern AI systems,” Kosinski said. “These models, trained to emulate human behavior, are improving rapidly at tasks requiring reasoning, emotional understanding and expression, planning, strategizing, and even influencing others.”
Despite its impressive performance, ChatGPT-4 still failed to solve 25% of the tasks, highlighting limitations in its understanding. Some of these failures may be attributed to the model’s reliance on strategies that do not involve genuine perspective-taking. For example, the model might rely on patterns in the training data rather than truly simulating a protagonist’s mental state. The study’s design aimed to prevent models from leveraging memory, but it is impossible to rule out all influences of prior exposure to similar scenarios during training.
“The advancement of AI in areas once considered uniquely human is understandably perplexing,” Kosinski told PsyPost. “For instance, how should we interpret LLMs’ ability to perform ToM tasks? In humans, we would take such behavior as evidence of theory of mind. Should we attribute the same capacity to LLMs?”
“Skeptics argue that these models rely on “mere” pattern recognition. However, one could counter that human intelligence itself is ‘just’ pattern recognition. Our skills and abilities do not emerge out of nowhere—they are rooted in the brain’s capacity to recognize and extrapolate from patterns in its ‘training data.'”
Future research could explore whether AI’s apparent theory of mind abilities extend to more complex scenarios involving multiple characters or conflicting beliefs. Researchers might also investigate how these abilities develop in AI systems as they are trained on increasingly diverse and sophisticated datasets. Importantly, understanding the mechanisms behind these emergent capabilities could inform both the development of safer AI and our understanding of human cognition.
“The rapid emergence of human-like abilities in AI raises profound questions about the potential for AI consciousness,” Kosinski said. “Will AI ever become conscious, and what might that look like?”
“And that is not even the most interesting question. Consciousness is unlikely to be the ultimate achievement for neural networks in our universe. We may soon find ourselves surrounded by AI systems possessing abilities that transcend human capacities. This prospect is both exhilarating and deeply unsettling. How to control entities equipped with abilities we might not even begin to comprehend.”
“I believe psychology as a field is uniquely positioned to detect and explore the emergence of such non-human psychological processes,” Kosinski concluded. “By doing so, we can prepare for and adapt to this unprecedented shift in our understanding of intelligence.”
The study, “(https://doi.org/10.1073/pnas.2405460121) Evaluating large language models in theory of mind tasks,” was published October 29, 2024.

(https://www.psypost.org/men-exhibit-stronger-sunk-cost-bias-than-women-when-mating-motives-are-activated/) Men exhibit stronger sunk cost bias than women when mating motives are activated
Jan 13th 2025, 18:00

Men are more prone than women to exhibit sunk cost bias—the tendency to persist with an investment despite its disadvantages—when exposed to romantic cues, according to new research published in the (https://doi.org/10.1093/jcr/ucae048) Journal of Consumer Research. Surprisingly this effect is not limited to romantic contexts but also extends to consumer behavior, suggesting that deep-seated evolutionary drives can subtly shape decision-making in various context.
The sunk cost bias refers to the tendency to persist with a decision or investment based on resources already spent, even when abandoning it might be the more rational choice. For example, someone might continue watching a movie they don’t enjoy simply because they’ve already invested an hour of their time. It is often viewed as irrational because the resources already invested (the “sunk costs”) cannot be recovered, and decisions should ideally be based on future outcomes rather than past expenditures.
Traditionally, explanations for this bias have focused on psychological and cognitive factors, such as the desire to avoid waste, fear of regret, or a need to justify prior decisions. However, some researchers suggest that sunk cost bias may not always be irrational. From an evolutionary perspective, committing to an investment might have been advantageous in contexts like mating and survival, where persistence and resource commitment signaled fitness and reliability to potential partners or ensured access to critical resources.
This evolutionary angle underpins the rationale for the study. The researchers proposed that sunk cost bias might serve an adaptive purpose in mating contexts, particularly for men, who historically adopted proactive and resource-intensive strategies to secure mates. They hypothesized that mating motives could trigger an implemental mindset—a focus on achieving specific goals—that heightens the tendency to stick with prior investments, even in unrelated domains like consumption.
To explore how mating motives influence sunk cost bias, the researchers conducted one field study and seven controlled experiments, six of which were pre-registered to ensure transparency.
The researchers began by exploring whether men and women differ in their susceptibility to sunk cost bias in a romantic context. They recruited 220 participants (114 women) from a Chinese online survey platform, with an average age of 30.7 years. Participants were randomly assigned to one of two conditions: a romantic relationship decision or a consumption decision.
In the romantic condition, participants imagined they had spent over a month chatting with a potential dating partner, sent virtual gifts, and arranged an in-person meeting. Before meeting, they learned of a more attractive and better-matched potential partner. They had to choose whether to stick with the original partner or meet the new one. In the consumption condition, participants imagined they had paid a non-refundable deposit for shoes but found the same shoes cheaper elsewhere. They decided whether to buy the shoes at the original store or switch to the cheaper option.
The goal was to see if men exhibited stronger sunk cost bias than women in romantic decisions but not in consumption decisions. This design controlled for potential confounding factors, like perceived morality, which was assessed using participant ratings. This study established that men were more likely than women to adhere to sunk costs in a mating scenario, setting the stage for broader investigations.
Building on Study 1, the researchers examined whether exposure to mating cues influenced sunk cost bias in unrelated domains, such as investment and consumption decisions. The sample consisted of 231 heterosexual participants (150 women), with an average age of 25.3 years, recruited from the United States via Prolific.
Participants were randomly assigned to one of two conditions: a mating cue condition or a control condition. In the mating cue condition, participants rated the attractiveness of images of opposite-sex individuals and imagined going on a romantic date with the most appealing person. In the control condition, participants rated images of apartments and imagined discussing rental details with the owner.
Afterward, participants were asked to make decisions in two scenarios. In the investment scenario, they had to decide whether to continue funding a plane project that was mostly complete but now outcompeted by a superior alternative. In the consumption scenario, they decided between attending a concert for which they had a $100 ticket or a preferred concert with a $50 ticket. Mating cues significantly heightened sunk cost bias among men in both scenarios but had no effect on women, reinforcing the role of mating motives.
The researchers designed Studies 3a and 3b to differentiate sunk cost bias, which involves prior investment, from status quo bias, which does not. Study 3a involved 420 Chinese university students (233 women, average age 23.1 years) recruited from a survey platform. Study 3b involved 561 participants (301 women, average age 31.1 years) from the Credamo platform.
In Study 3a, participants completed a task to earn a lottery opportunity (prior investment condition) or were given the lottery directly (no prior investment condition). Mating cues were manipulated similarly to Study 2. Participants then decided whether to switch to a lottery with better odds. Results showed that men’s sunk cost bias increased in the prior investment condition when exposed to mating cues, while no such effect was found in the no-investment condition.
Study 3b used a restaurant reservation scenario. In the prior investment condition, participants had paid a deposit; in the no-investment condition, they had made a free reservation. As in Study 3a, mating cues heightened sunk cost bias for men in the prior investment condition but had no effect in the no-investment condition, confirming the distinction between sunk cost and status quo biases.
To explore the mechanism behind mating cues and sunk cost bias, the researchers conducted Studies 4a and 4b, recruiting 539 participants (301 women, average age 30.5 years) and 551 participants (302 women, average age 30.6 years), respectively, from Credamo.
In Study 4a, participants described an upcoming event they were planning and completed a mating cue manipulation as in earlier studies. An implemental mindset was measured with items assessing participants’ focus on goal-directed behaviors (e.g., planning actions). Results showed that mating cues heightened an implemental mindset in men but not in women.
In Study 4b, participants’ implemental mindset was manipulated. Those in the strengthened condition listed steps to address a hypothetical problem, while those in the control condition described the problem. All participants then made a sunk cost decision about continuing a plane project. Results showed that an implemental mindset increased sunk cost bias for both men and women, supporting its role as a mediator.
Study 5 used a process-by-moderation approach to confirm the role of implemental mindset in linking mating cues and sunk cost bias. The sample included 572 participants (305 women, average age 31.8 years) recruited from Sojump. Participants were exposed to mating or control cues and then completed a task to manipulate their implemental mindset (e.g., choosing between two laptops to activate goal-oriented thinking).
Participants then made a sunk cost decision about continuing to watch a boring movie after investing an hour. In the control condition, mating cues increased men’s sunk cost bias. However, in the strengthened implemental mindset condition, mating cues had no effect, as all participants exhibited heightened sunk cost bias. This result confirmed that the implemental mindset drives the observed effects.
The final study applied these findings in a real-world context. The researchers collaborated with a university coffee shop, recruiting 240 Chinese students (120 women) over seven days. Participants were offered paid membership cards (5 RMB) with a 20% discount on coffee for two weeks. The cards featured either a romantic design (mating cue) or a neutral design (control).
The researchers tracked card usage and conducted follow-up surveys to measure participants’ motivations and behaviors. Results showed that men exposed to romantic cards used their memberships more frequently, demonstrating stronger sunk cost bias when mating cues were present. Women’s behavior was unaffected by the romantic design, highlighting the gender-specific effects of mating motives on investment persistence.
Together, the findings provide evidence that mating motives can significantly influence decision-making by activating an implemental mindset, particularly among men. This mindset drives a stronger commitment to prior investments, manifesting as sunk cost bias, even in contexts unrelated to mating.
The research highlights fundamental gender differences rooted in evolutionary mating strategies, where men are more likely to exhibit goal-directed persistence in response to mating cues. These effects extend beyond romantic scenarios into consumer behavior, showing how deep-seated psychological mechanisms shape everyday choices.
The findings also have real-world implications for marketing and consumer behavior, the researchers said. For instance, marketers could use romantic cues to boost men’s commitment to loyalty programs or products where upfront investments are required. However, the researchers added that policymakers and consumers should remain vigilant about how such tactics might exploit psychological biases, leading to irrational financial decisions.
The study, “(https://doi.org/10.1093/jcr/ucae048) He Loves the One He Has Invested In: The Effects of Mating Cues on Men’s and Women’s Sunk Cost Bias,” was authored by Rui Chen, Hao Sun, Zhaoyang Guo, and Haipeng (Allan) Chen.

(https://www.psypost.org/new-research-supports-brain-cell-transplantation-as-a-treatment-for-some-neurological-disorders/) New research supports brain cell transplantation as a treatment for some neurological disorders
Jan 13th 2025, 16:00

Astrocytes — named for their star-like shape — are (https://www.ncbi.nlm.nih.gov/books/NBK545142/) a type of brain cell as abundant as neurons in the central nervous system, but little is known about their role in brain health and disease.
Many neurological diseases are caused by or result in the loss of cells in the central nervous system. Some diseases are (https://doi.org/10.1177/09636897221105499) a result of the loss of specific cells, such as the loss of motor neurons in amyotrophic lateral sclerosis (ALS), the loss of dopaminergic neurons in Parkinson’s disease and the loss of GABAergic neurons in Huntington’s disease.
For other neurodegenerative conditions, like Alzheimer’s disease, a key hallmark is the general loss of cells in brain regions responsible for memory formation.
Although many brain diseases are marked by the loss of specific cells, a common link among these diseases is the loss of astrocytes. Interestingly, in some animal studies involving cases such as ALS, introducing disease-causing mutations selectively in astrocytes alone (https://doi.org/10.1016/j.tins.2024.02.008) produces ALS symptoms and disease progression.
The left image shows a microscopic picture of typical astrocytes in pink — the star-like skeletons are shown in green. On the right is a diagram showing healthy astrocytes above and a diseased astrocyte in different degenerative diseases. (A.H. Fok and S. Chierzi)
Transplantation therapy
Emerging evidence indicates that astrocytes take part in major functions of the brain, including homeostasis and neural network modulation that are (https://doi.org/10.1038/s41392-023-01628-9) essential to everyday cognition. A functioning brain requires healthy astrocytes, and finding strategies to heal or replace damaged astrocytes could help in the treatment of neurological diseases.
Cell replacement therapy involves transplanting functional cells in patients. In recent years there have been exciting developments in this area with respect to astrocyte transplantation in animal disease models, with one approach even moving to (https://doi.org/10.1177/09636897221105499) early clinical trial in ALS patients. While there have been some promising outcomes, treatment success varies from one study to the other.
Our recent study, published in The Journal of Neuroscience, examines (https://doi.org/10.1523/JNEUROSCI.0544-22.2023) how transplanted astrocyte integrate into the recipient central nervous system. We studied the types of transplanted astrocytes, timing of treatment and routes of transplantation.
Preparing astrocytes
First, we prepared astrocyte cultures in petri dishes by extracting immature astrocytes from the cerebral cortex of newborn mice and expanding the cell population. To track the development of transplanted astrocytes following their delivery to recipient mice, we used astrocytes from genetically modified mice in which astrocytes glow red, and they are transplanted into the brain of mice where astrocytes glow green.
We found that the transplanted astrocytes could survive for up to one year after transplantation, developing normally and integrating into the recipient brain just like the native astrocytes, with just minor differences.
Astrocytes depend on their capability to sense signals and exchange materials within the brain environment through molecules such as receptors and ion channels located on their cell surface. Transplanted astrocytes displayed comparable numbers of such receptors and channels and possessed similar sizes and complexity when compared to native astrocytes.
Transplanted astrocytes do appear to take some time to catch up to and perfectly match astrocytes in the recipient mice in terms of the production of these receptors and ion channels.
Transplanted cortical astrocytes (magenta) can integrate in the host cerebral cortex, populated by green astrocytes. Stars indicate the position of neurons ‘hugged’ by transplanted astrocytes. (A.H. Fok and S. Chierzi)
Source, type and location
Intriguingly, we also found that the integration of transplanted astrocytes into the recipient is affected by the age of the mouse, which reflects the maturity of the cellular environment the astrocytes are transplanted into. When astrocytes were transplanted to an infant mouse, they could migrate and spread more extensively in the host brain. However, when astrocytes were transplanted into a young adult mouse, they were confined to the site of transplantation.
Astrocytes in different regions of the brain and the spinal cord display very different features. We were interested in seeing how astrocytes from one region of the brain integrated into a different region. Astrocytes prepared from the cerebral cortex ended up developing into cortical astrocytes even when placed into the cerebellum.
Therefore, the source and type of astrocytes being transplanted makes a difference, and this intrinsic programming of astrocytes needs to be considered when thinking about astrocyte replacement therapy.
Exciting potential
In recent years, increasing studies have been conducted to investigate the potential of astrocyte transplantation. Similar to our findings, transplanted astrocytes have been found to form (https://doi.org/10.1093/cercor/bhw213) normal contacts with neuronal synapses and are functioning normally. Astrocyte transplantation has also been shown (https://doi.org/10.1177/09636897221105499) to promote brain plasticity and regeneration following injury and in different animal models of neurological diseases.
Therefore, it presents a promising and exciting strategy to treat neurological diseases. By answering principle questions regarding how transplanted astrocytes integrate in the host, our research can support the development of more effective cell therapies that can improve the quality of life of patients.
 
This article is republished from (https://theconversation.com) The Conversation under a Creative Commons license. Read the (https://theconversation.com/new-research-supports-brain-cell-transplantation-as-a-treatment-for-some-neurological-disorders-237376) original article.

(https://www.psypost.org/maladaptive-personality-traits-linked-to-hypersexual-disorder-in-men-study-finds/) Maladaptive personality traits linked to hypersexual disorder in men, study finds
Jan 13th 2025, 14:00

A new study indicates that men with hypersexual disorder may have higher levels of maladaptive personality traits, such as negative affect, detachment, psychoticism, antagonism, and disinhibition, compared to healthy men. The paper was published in (https://doi.org/10.1556/2006.2023.00029) the Journal of Behavioral Addictions.
Mental health professionals have long been noting the existence of people preoccupied with sexual behavior to the extent that created serious problems in their daily functioning. Such individuals show an excessive preoccupation with sexual fantasies, urges, or behaviors that cause significant distress and impairment. The term hypersexual disorder was proposed to describe this condition. It differs from just having a strong sex drive by the presence of distress and compulsivity in one’s sexual actions.
Individuals with hypersexual disorder tend to engage in compulsive sexual activities such as frequent masturbation, pornography use, promiscuity, or pursuing sexual encounters to the detriment of their relationships, work, or personal responsibilities. It is often associated with a loss of control, where attempts to reduce or stop these behaviors are unsuccessful. That is why it is generally considered an impulse control disorder.
Study author Jannis Engel and her colleagues wanted to better understand the relationship between personality factors and hypersexual disorder. They conducted a study in which they compared a group of men with hypersexual disorder with men not suffering from this disorder on personality domains described by an assessment of maladaptive personality traits, the PID-5-BF.
This assessment assesses five broad domains of personality dysfunction – Negative Affectivity, Detachment, Antagonism, Disinhibition, and Psychoticism. Negative Affectivity is characterized by intense emotional distress, anxiety, or fear. Detachment involves social withdrawal, emotional coldness, and avoidance of close relationships. Antagonism is marked by hostility, manipulativeness, and a disregard for others’ needs or feelings. Disinhibition reflects impulsivity, recklessness, and difficulty maintaining self-control. Finally, Psychoticism describes a tendency to have eccentric thoughts, perceptions, or behaviors that deviate significantly from reality.
Study participants were 47 men who self-identified as having hypersexual disorder, and 41 men without this disorder matched for age with the hypersexual disorder group. Participants’ average age was 37-38 years.
The hypersexual disorder group was identified through a combination of self-report measures and clinical interviews, ensuring they met the diagnostic criteria for the condition. Participants with significant mental health issues, such as psychotic disorders or severe head injuries, were excluded to maintain the study’s focus on hypersexuality. The comparison group of men without hypersexual disorder was recruited through advertisements and underwent similar screening to confirm they did not exhibit hypersexual behaviors.
Study participants completed assessments of maladaptive personality traits (the Personality Inventory for DSM-5), hypersexual disorder symptoms (the Hypersexual Behavior Inventory-19), and sexual addiction symptoms (the Sexual Addiction Screening Test – revised).
The results showed that men with hypersexual disorder scored higher across all five domains of personality maladjustment compared to their counterparts. These differences were particularly pronounced in the domains of disinhibition and detachment.

Disinhibition: Men with hypersexual disorder demonstrated higher levels of impulsivity, distractibility, and irresponsibility. These traits align with previous research suggesting that impulsivity plays a central role in behavioral addictions.
Detachment: This group also showed increased levels of social withdrawal, anhedonia (reduced ability to experience pleasure), and suspiciousness. These traits could reflect a tendency to avoid emotional intimacy, potentially leading to reliance on sexual behavior as a coping mechanism.
Negative affect: Men with hypersexual disorder exhibited heightened emotional instability, including hostility, separation insecurity, and perseveration (rigidity in behavior). This aligns with findings that individuals with hypersexual disorder often struggle with stress and emotional dysregulation.
Antagonism: Traits such as attention-seeking, deceitfulness, and grandiosity were also more prevalent in the hypersexual disorder group, suggesting interpersonal challenges that may exacerbate feelings of isolation.
Psychoticism: Elevated scores in this domain pointed to unusual thought processes and behaviors, which may contribute to maladaptive coping strategies.

Despite these differences, a logistic regression analysis indicated that no single personality domain could reliably predict whether an individual would fall into the hypersexual disorder group.
“In sum, the findings of the study underline the extent of personality maladjustment in men with HD. Interpersonal difficulties which men with HD [hypersexual disorder] frequently experience can contribute to clinically relevant levels of distress and adverse consequences reported by affected individuals,” the study authors concluded.
The study sheds light on the personality correlates of hypersexual disorder symptoms. However, it should be noted that the study’s design does not allow for causal inferences. Additionally, the study included a very small sample of men. Results from larger or more representative groups might differ.
Future research should aim to include more diverse samples, encompassing individuals from different cultural backgrounds, genders, and sexual orientations. Longitudinal studies would also help clarify whether personality maladjustments are a cause or consequence of hypersexual disorder.
The paper, “(https://doi.org/10.1556/2006.2023.00029) Personality dimensions of compulsive sexual behavior in the Sex at Brain study,” was authored by Jannis Engel, Marie Carstensen, Maria Veit, Christopher Sinke, Jonas Kneer, Uwe Hartmann, and Tillmann H.C. Kruge.

(https://www.psypost.org/generative-ai-chatbots-like-chatgpt-can-act-as-an-emotional-sanctuary-for-mental-health/) Generative AI chatbots like ChatGPT can act as an “emotional sanctuary” for mental health
Jan 13th 2025, 12:00

Could generative AI chatbots make a meaningful contribution to mental health care? A study published in (https://doi.org/10.1038/s44184-024-00097-4) npj Mental Health Research suggests they could. Researchers conducted interviews with individuals who used chatbots such as ChatGPT for mental health support and found that many participants reported experiencing a sense of emotional sanctuary, receiving insightful guidance, and even deriving joy from their interactions.
Generative AI chatbots are advanced conversational agents powered by large language models, such as OpenAI’s ChatGPT or Google’s Gemini. Unlike rule-based chatbots, which rely on preprogrammed scripts and decision trees, generative AI chatbots are trained on vast datasets to understand and produce human-like text. This enables them to engage in nuanced and flexible conversations, answer complex questions, and provide tailored responses based on context.
In mental health contexts, generative AI chatbots represent a novel approach to providing support. They are available 24/7, nonjudgmental, and capable of engaging in dynamic, empathetic interactions. These characteristics make them appealing to individuals who may face barriers to traditional therapy, such as cost, stigma, or geographic limitations. Despite their growing use, however, little is known about how people experience these tools in real-world mental health scenarios.
“I’ve long been convinced that technology holds great promise to address the global mental health crisis—nearly a billion people worldwide suffer from mental disorders, the overwhelming majority of whom don’t get adequate treatment—but I’ve also been daunted by the low effectiveness of mental health apps despite a decade of development,” said Steven Siddals, who conducted the study in collaboration with King’s College London and Harvard Medical School.
“Like so many people, I was blown away by ChatGPT in late 2022, and I started hearing more and more about mental health use cases in 2023. It didn’t take much testing to realize this is an entirely new capability, with real potential, that will need a lot of research to understand its implications.”
The research team recruited nineteen participants from diverse backgrounds, ranging in age from 17 to 60, with a mix of male and female users from eight countries. Participants were required to have had at least three meaningful conversations with a generative AI chatbot about mental health topics, each lasting at least 20 minutes. Recruitment was conducted through online platforms, including Reddit and LinkedIn, and participants voluntarily joined without receiving compensation.
The researchers conducted semi-structured interviews, allowing participants to share their experiences in their own words. Questions addressed topics such as their initial motivations for using chatbots, the impact on their mental health, and comparisons to other forms of support. Conversations were recorded, transcribed, and analyzed using a thematic analysis approach, which involved coding participant responses and grouping them into broader themes.
Siddals was surprised by “the depth of impact it had on people. Participants described their interactions with AI for mental health support as life changing, for example in how it supported them through their darkest times, or helped them heal from trauma.”
The researchers identified four major themes that captured participants’ experiences:
Emotional sanctuary
Many participants described generative AI chatbots as a safe, nonjudgmental space where they could express their feelings without fear of rejection. The chatbots were perceived as patient and empathetic, helping users process complex emotions and cope with difficult life events. One participant remarked: “Compared to like friends and therapists, I feel like it’s safer.”
However, frustrations arose when the chatbot’s safety protocols disrupted conversations, leaving some users feeling rejected during moments of vulnerability. For example, some participants reported that when discussing sensitive or intense emotions, the chatbots abruptly reverted to pre-scripted responses or suggested seeking human help, which could feel dismissive.
“Ironically, the only distressing experiences reported by our participants were the times when the AI chatbot left them feeling rejected in moments of vulnerability, because its safety guardrails were activated.”
Insightful guidance
Participants valued the chatbots’ ability to offer practical advice and new perspectives, particularly regarding relationships. For example, one user credited a chatbot with helping them set healthier boundaries in a toxic friendship. Others found the chatbots effective at reframing negative thoughts or providing strategies for managing anxiety.
However, the level of trust in this guidance varied. While some participants found the advice empowering and life-changing, others were skeptical, particularly when the chatbot’s responses seemed generic or inconsistent.
Joy of connection
Beyond emotional support, many participants experienced a sense of enjoyment and companionship from interacting with chatbots. For many users, interacting with a chatbot brought a sense of companionship and even happiness, particularly during periods of loneliness. The conversational style of generative AI made interactions feel engaging and human-like, which some participants found awe-inspiring.
Additionally, a number of participants noted that using chatbots helped them build confidence in opening up to others, strengthening their real-life relationships.
“[It] reduced my inhibition to open up to people… I don’t think I would have had this conversation with you maybe year before, when I was dealing with my depression,” one participant explained.
The AI therapist?
Comparisons between generative AI chatbots and human therapists were common. Some participants found the chatbots to be valuable supplements to therapy, using them to prepare for sessions or process thoughts between appointments. Others turned to chatbots because therapy was inaccessible or unaffordable.
However, participants also noted limitations, such as the chatbot’s inability to lead the therapeutic process or provide deep emotional connection. The lack of memory and continuity in conversations was another frequently cited drawback.
“They forget everything,” a participant explained. “It’s sad… When someone forgets something important, it hurts.”
 
Siddals also highlighted the “creativity and diversity in how people used” AI chatbots. For instance, one participant used the chatbot to assemble fictional characters with contrasting perspectives for support during a breakup, while another recreated an imagined, healing conversation with an estranged parent to address unresolved guilt and find emotional closure.
“If you’re suffering emotionally, you might be able to find meaningful emotional support from ChatGPT and other generative AI chatbots – at no cost, at any time of day or night, in a judgement-free space,” Siddals told PsyPost. “Our study participants experienced it as an ’emotional sanctuary’ for processing feelings and healing from trauma, as a source of insightful guidance (especially about relationships), and as a joy to connect with, in a way that bears comparison with human therapy. Just bear in mind that this is emerging technology and not well understood, so if you do use it, you’ll need to use it carefully and take responsibility for your safety.”
While the study offers valuable insights, it also has limitations. The small sample size and reliance on self-selected participants mean the findings may not represent the broader population. Most participants were tech-savvy and from high-income countries, potentially excluding perspectives from those who face the greatest barriers to mental health care. Additionally, the qualitative nature of the study does not provide quantitative measures of effectiveness or safety.
“If you’re interested to try these tools, it’s important to know that nobody really understands how generative AI is able do what it does, not even the companies that built it,” Siddals noted. “While nobody in our study reported serious negative experiences, AI chatbots are known to make things up (“hallucinate”) at times, and examples have been reported of AI chatbots responding inappropriately when used for mental health or companionship.”
Future research should explore the long-term impacts of generative AI chatbots on mental health outcomes, particularly through large-scale, controlled studies. It will also be important to investigate how these tools perform across diverse populations and mental health conditions.
“I hope this research will help to get generative AI for mental health on the agenda as one of the more promising developments in the field,” Siddals said. “We urgently need: More research, to understand safety and effectiveness, for example with large scale longitudinal studies to assess the impact on different conditions and populations. More innovation, to develop better safety paradigms and better ways to connect the people who need mental health support with the tools that could help them, at scale. More experimentation from clinicians on how these tools can complement therapy to help their clients.”
“This is a fast-moving area, with constant evolution of the technology and rapid adoption – which only adds to the urgent need for more research on real-world usage to understand this new capability and find out how to deploy it safely and effectively.”
The study, “(https://doi.org/10.1038/s44184-024-00097-4) ‘It happened to be the perfect thing’: experiences of generative AI chatbots for mental health,” was authored by Steven Siddals, John Torous, and Astrid Coxon.

(https://www.psypost.org/psychology-study-finds-self-control-drives-perceptions-of-power-and-leadership/) Psychology study finds self-control drives perceptions of power and leadership
Jan 13th 2025, 10:00

A series of studies published in the (https://doi.org/10.1037/pspi0000457) Journal of Personality & Social Psychology suggests that individuals who exhibit high self-control are perceived as more powerful and are more likely to be conferred power than those with low self-control.
How self-control shapes power perception and conferral is an ongoing debate in the power literature. While low self-control, linked to disinhibition, can signal power, high self-control reflects agency through goal-directed actions and resource management, leaving it unclear which behavior observers view as a stronger indicator of power.
Power perception influences leadership preferences and resource allocation in both personal and professional settings. Observers infer power from behavioral cues like competence and assertiveness, but the connection between self-control and power is ambiguous. In this work, Shuang Wu and colleagues clarify how self-control shapes judgments of agency and power/leadership suitability.
A series of 7 studies used a combination of hypothetical scenarios, real-life recollections, and controlled experimental manipulations. Participants were recruited primarily through online platforms, with a total sample size of approximately 1,953 participants across all studies.
Study 1 examined whether participants perceived individuals with high self-control as more powerful in a group leadership context. Participants (n = 201) evaluated two hypothetical group members with contrasting levels of self-control, manipulated through their responses to New Year’s resolution prompts. One candidate demonstrated high self-control by stating they were maintaining their resolution, while the other admitted to struggling with theirs. Participants allocated leadership votes between the two candidates and rated their perceived power.
Studies 2a (n = 224) and 2b (n = 448) extended this to real-world settings, asking participants to recall incidents where colleagues exhibited high or low self-control. Study 2b added a baseline condition, where participants described a colleague’s typical behavior. Participants then rated these colleagues on power, assertiveness, competence, morality, and warmth.
Studies 3 and 4 manipulated decision speed to disentangle the effects of self-control and inhibition. Participants (n = 200 in each study) were presented with scenarios where targets demonstrated self-control either quickly or deliberately. Perceptions of power and leadership suitability were then measured.
Study 5 investigated goal alignment by presenting participants (n = 200) with scenarios where individuals performed identical actions but had different goals (aligned vs. misaligned with long-term objectives). Participants rated the targets on power and related traits.
Study 6 focused on goal ambition. Participants (n = 480) evaluated individuals who either exceeded modest goals or failed to meet ambitious ones, despite performing the same action. Ratings of perceived power and willingness to confer leadership roles were collected.
The studies consistently showed that high self-control signals power. In Study 1, participants allocated more votes to candidates demonstrating high self-control, perceiving them as more powerful and leader-like.
Studies 2a and 2b confirmed that self-control influences perceptions in real-life contexts. Recalling a high self-control incident made participants perceive colleagues as more powerful and suitable for leadership. Study 2b revealed that low self-control reduced power perceptions compared to a baseline, while high self-control elevated them.
Studies 3 and 4 showed that the effect of self-control on power perception persisted regardless of decision speed. Participants viewed high self-control as powerful whether decisions were made quickly or deliberately, highlighting that observers prioritize goal alignment over deliberative processes.
Study 5 emphasized the importance of goal alignment. Targets performing identical actions were perceived as more powerful when those actions aligned with long-term goals. This demonstrated that power perception is tied to the alignment between actions and overarching objectives.
Study 6 revealed the role of goal ambition. Individuals who exceeded modest goals were seen as more powerful than those who failed to meet ambitious goals, despite identical actions. This finding underscored that achieving goals—rather than merely setting them—drives perceptions of self-control and power.
Across all studies, perceived competence and assertiveness emerged as the strongest mediators, linking self-control to power perception and power conferral. Morality played a more limited role, directly influencing power conferral in some contexts but not consistently mediating power perception.
Overall, this research demonstrates that high self-control is a critical signal of power. Observers prioritize competence, assertiveness, and goal alignment when evaluating an individual’s suitability for leadership or influential roles.
The experimental designs may limit the generalizability of findings to real-world contexts, where relationships and histories between individuals can affect power dynamics.
The research, “(https://doi.org/10.1037/pspi0000457) Self-Control Signals and Affords Power,” was authored by Shuang Wu, Rachel Smallman, and Pamela K. Smith.

Forwarded by:
Michael Reeder LCPC
Baltimore, MD

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